This course pretty much restored my faith in the online courses. Hands down, this is the best online course I have ever had, not only in astronomy. This course had everything to satisfy my needs:

*I had an opportunity to analyse actual astronomical data, which made me feel like a small child again

*I have learned to program in python for scientific reasons, which I previously only used for the backend purposes. The python skills also helped my in my computer modelling studies at the university.

*Also, even though I am working with SQL pretty much every day, this course still managed to teach me some new concepts, and understand joins better. This course, even that it's on the astronomy, managed to explain SQL much better than the conventional lectures.

Regarding the lecturers, both lecturers seemed extremely passionate in what they are talking about, and also managed to explain everything in very concise manner.

Also, I really enjoyed the quizzes, since they do not directly ask what was mentioned in the video, but the questions are twisted a bit to make you actually think for answer.

Finally, this course presents a lot of further research to investigate yourself. This ranges from scientific papers to the links to classify galaxies.

Overall, in my opinion, this course was truly amazing and made my weekends (that's when I had some time to do the exercises) worthwhile. Would definitely recommend it to anyone starting their journey in astronomy, astronomical data, python programming. If you are quite familiar with machine learning concepts and python though, this course might be a bit too easy for you. Though actual astronomical data might spice things up a little.

I really enjoyed this course. It is very well structured, with a good progression in the complexity which make it accessible even for people who have quite no skills in Python or SQL, and who are no astronomers (like me). The teachers use a wide range of astronomical subjects to illustrate the different techniques used in data analysis. They propose examples and exercises based on real datasets, which is fabulous for people like me who don't have access to such datasets (or can have access to, but no comprehension of what they show).

Teachers are also reactive in the forums, which is much appreciated. And, for a non-english speaking person, the subtitles are very usefull. The Grok interface is incredibly easy to use, with, again, a progressive complexity in the exercises, and great explanations at each step.

If I tried to find something to improve, I would say: make more obvious how the learned techniques can actually help and improve astrophysical research, maybe with more examples of publications or concrete results obtained in the research field. But it's just quibble over details :-) The interviews in the bonus are very interesting.

So, congratulations for this great work, and thank you for opening a little bit the door of your laboratory :-). Now, more than ever, I hope to work in this domain one day.

Gostei demais das aulas condizentes com a posterior apresentação do conteúdo e aplicação dos exercícios. Acredito que alguns deles contém alguma falha na avaliação como uso de funções que não foram apresentadas, isso implica que um estudante atento possa pensar que não pode usar aquela função (como uma trapaça) ou mesmo um estudante ainda leigo na específica tarefa. Acho isso um probleminha pontual e que não interferiu de maneira alguma no aprendizado, afinal, a solução está lá para ser verificada.

O conteúdo é bem abrangente e aborda de maneira geral uma gama interessante de assuntos da astrofísica. Achei que no começo iria trabalhar somente com pulsares hehe. O que mais me instigou foi a aplicação das técnicas passadas a astrofísica, o seu embasamento e suas limitações. Foi um apanhado geral e pode ser considerado como introdutório.

Finalmente sei por onde continuar porque ter começado aqui foi um acerto e tanto!

An excellent introduction to the use of software in handling the vast quantities of data generated in astronomy. It isn't possible for a course intended to take a few hours per week to cover things in great depth.

Some interesting astronomy is covered. There are astronomy quizzes but not much physics / astronomy knowledge is necessary.

This is mainly a programming course. The 1hr estimate for Python exercises is optimistic especially for students who have little programming experience. Ideally, students should have done an introductory Python course. The importance of software performance when handling large amounts of data is emphasised.

The course also covers SQL - a useful skill, but no background necessary IMO.

The final two weeks cover machine learning applied to astronomy: how it can be useful, some pitfalls, and checking the machine learning model's quality.

I highly recommend this course if you are curious about some of the big data tools and techniques used in astronomy. Especially if you already use Python a bit and want to try out some machine learning and other astronomy related python tools. I wanted to learn something about astronomy and to play with the data - the cross-matching and machine learning were my favourite parts of the course. As usual, I'm in awe about what we know about the universe - so to casually play with data on Active Galactic Nuclei for example, or redshifts of galaxies was great fun, educational and just brilliant. I've got things I want to try out now, before starting another course. Oh, and the two tutors present the material very well on the videos.

This is a very interesting introduction to data analysis and machine learning for astronomy. The hands-on approach makes the course quite engaging.

The course is well structured and presented. The lectures are interesting and the explanations clear. The course materials are well chosen to illustrate what is being taught in the lectures. The development environment (Grok) is usable and glitch-free.

The choice of programming language, Python3, looks quite right to me. Python has become the "new normal" in astronomy. It offers an easy learning curve and a myriad of well tested modules which are available for free.

I really enjoyed this course and I would recommend it to any one with an interest in this or related subjects.

This course was such a big help to me . I leaned about astronomy as well as develop some skills of data science which might help me in other platforms as well. The explanation was good and I liked all the real time problems .

One thing is that providing the solutions of the code makes it easy for us to solve the coding problems and it's very intimidating to look at the solution if we're stuck somewhere in the coding. It's a kind of a downside when viewed in a neutral perspective .

Other than that the content was really good and hopefully advanced courses of this course will be provided to us.

Cheers . Thank you!

This is a great course on data-driven science introducing most important aspects ranging from data collection, data access and management to data analyses. It addresses issues that I was not aware of when it comes to huge data sets such as computer memory and CPU time. It was thus rather interesting to me to see some ways of handling these issues. Last but not least, this course remains free and accessible to everyone as was originally the philosophy of MOOCs or at least some platforms. I was told this is a trademark of astronomers (free access to data and knowledge). Thanks a lot!

This course is absolutely for beginners. Very minimal knowledge of python is required. The course is perfectly designed for beginners. The contents are present in so lucid manner and the instruction to complete the activities are so easy to follow. If you are interested in learning python a bit and as well apply them to build concepts of astronomy, the boom, you are at the right place! Go ahead and get yourself some pretty pictures of the universe or be happy with how you make the first machine learning regression/classification of galaxies. Whatever pleases you!

Extremely fun and helpful.

The instructors do an excellent job explaining fun astronomy concepts while relating them to something from Computer Science, leading to a really good learning experience in both topics.

The Coding section isn't hard to catch onto, and the problems, despite their apparent complexity, are explained well enough that even novice Python programmers can solve them.

If you love Astronomy and want to learn more about Computer Science or want to get your feet wet in Data Science with Python, this is a really great stepping stone to begin learning.

Just finished this wonderful course, it teaches (mostly in Python) the basics of how to apply certain techniques of data handling, processing, and analysis, in the realm of Astronomy, which has vast amounts of collected data and which I've loved all my life as a hobbyist! This knowledge is very useful and can be extended to many other scientific fields. The course has a great mix of theory and hands-on exercises (with a great supporting online coding platform), and encourages people to continue reading and experimenting on their own.

Wonderful course, really enjoyed my time exploring it. Moreover, it got me interested in machine learning. All I can say is I'm thirsty for more. Clear. Straight-forward, easy to grasp, practical and up-to-date. Great Job!

There were several tiny lines in the descriptions on Grok that could be made better (to make things [Even!] clearer and easier to understand, or just to avoid grammar or spelling mistakes).

Nevertheless this does not affect my view upon this course or my rating, since the course is straight-up amazing. Thank you!

First, I enjoyed the course, thank you. I am a computer scientist by profession, and came here to learn how astronomers perceive data analysis software in their pursuit. This course not only introduced me to how software is used for data analysis in astronomy, but also gave me insights on challenges the community is (or could potentially be) facing. Course is well-paced on theoretical and programming fronts, along with necessary hand-holding whenever required. Hoping to see an advanced version of this course. Thank you again.

It's been an amazing and educative journey. Besides sharping my Python skills, the Astropy and Numpy library are really a wealth of knowledge that is worth using. Machine learning was new for me, specifically decision trees. I got some knowledge 20 years ago about neural networks and fussy logic, but his was something new. All in all, the instructors and assisting staff showed their expertise both in the programming part as well as in the astronomical domain. Really a recommended course for those who love both domains!

I enjoy learning about recent advances in astronomy. Since astronomy isn't my vocation, I usually have to settle for a view from the sidelines. Although that may still be the case, I think this course has taken me to a seat in the front row. Moreover, I learned computational thinking, which is immensely useful in my vocation. I couldn't have asked for a better way to marry my love of astronomy with practical knowledge of modern day tools to extract, store, and manipulate data and glean useful insights from the data.

It was a great course. A basic understanding of how python works and few of its modules is enough for this course. Astronomy lovers and a techie must combine their both the skills and learn how to take all the openly available data from different telescope available online and come to their own conclusion from it. Operating a FITS file, image stacking, image processing, DBMS, SQL query, editing database, reading database, taking output from a big database using classifiers, finding distance to stars and much more.

I enjoyed this fusion of programming with Astronomy topics. Note that the exercises use the Python programming language (no substitutes permitted), fairly generic Structured Query Language (SQL) for databases, numpy (science math tools) Python library, scikit-learn (machine learning) Python library, and matplotlib (math & plotting) Python library.

I highly recommend this course, even if you are already experienced in a subset of the above.

Would be interesting: a 2nd more advanced course.

What I liked about the course was the graded programming assignments, which help to introduce a person to machine learning techniques and other problems in astronomy data processing. Being a physics student by formal education and a star gazer too, I am familiar with the theory but was always curious about how to they measure distances, how do they measure red-shifts etc when the distant galaxies are themselves so faint. This course helped me understand these stuff....

Very good. I like how the course is structured - every week we first learn the basic knowledge of the astronomical objects in concern, followed by hands-on coding practice on solving problems, and learning the programming language and/or machine learning algorithm at the same time. It is really suitable for astronomy students like me, to get to know the additional data science and computational skills necessary for entering a field that uses big data all the time.

Very interesting and inspiring course. I work in the world of economics and statistics but I always had passion for astronomy. This course gave me an idea of the possible data applications in this field and an intuition of some of the modern astronomical challenges . It also stimulated me to review some of the machine learning techniques I had previously studied. I definitely recommend it and I would be happy to take a follow-up course on this.

Excellent Course.I really really enjoyed my journey throughout the course.Got to learn so much from the course whether its regarding to SQL or to python.Course also offers great insights into developing and structuring Machine Learning Projects.The Science part was absolutely amazing and thrilling ,the lectures were brilliant as well as concise and both the instructors were so good.Its been a beautiful learning journey for me.

Exceptional course. From a computer science point of view provides a very good example of scientific application of several topics (complexity, search algorithms, databases, practical Python and SQL exercises, machine learning...). From an Astronomy perspective, it shows a simple but powerful tool set to work with data. In addition the interviews with astronomers provide a good insight about the what is the actual work.

Thank you for a very interesting, educational, and ofttimes challenging course. I suspect the instructors and mentors have introduced me to only the tip of the iceberg - 98% of data-driven astronomy lies below the surface and inside enormous datasets/databases. It almost makes me wish life had taken a different course and brought me to this fascinating subject. I would look forward to any further courses from you.

Simply superb, I'm aspiring to pursue an academic career in AstroInformatics and I can see this course serving as a great foundation. Not only were numpy/SQL/scikit-learn tutorials were brilliant from a computational perspectively, but the exposure to concepts in astronomy/astrophysics were insightful too! Would recommend this course to anyone in astronomy, or a CS person wishing to get into astronomy.

One of the best courses I have taken. The instructors are fantastic! This course is like a 500 page novel that you cannot put down and now you are on the last 10 pages. I do not want this course to end!! It was such pleasure to go through the videos and problems!!

Sincere thanks to Professor Tara Murphy and Dr. Simon Murphy !! Good on ya mates!! Please have a follow-on course!!